Harri Lähdesmäki

Aalto SCI Computer Science Konemiehentie 2

Research activity per year

Artistic and research interests

I work on computational biology and probabilistic machine learning with applications in biomedicine.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

Keywords

Computational biology
Machine learning
Deep generative models
Bioinformatics
Artificial intelligence
Probabilistic modelling

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114 Article
37 Conference article in proceedings
7 Working paper
6 Meeting Abstract
More

Bayesian Basis Function Approximation for Scalable Gaussian Process Priors in Deep Generative Models
Balik, M. Y., Sinelnikov, M., Ong, P. & Lähdesmäki, H., 2025, Proceedings of the 42nd International Conference on Machine Learning. JMLR, p. 2673-2696 24 p. (Proceedings of Machine Learning Research; vol. 267).
Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

Open Access
File
5 Downloads (Pure)
E(3)-equivariant models cannot learn chirality: Field-based molecular generation
Dumitrescu, A., Korpela, D., Heinonen, M., Verma, Y., Iakovlev, V., Garg, V. & Lähdesmäki, H., 2025, 13th International Conference on Learning Representations, ICLR 2025. Curran Associates Inc., p. 59765-59799 35 p.
Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

Open Access
File
17 Downloads (Pure)
High-Dimensional Bayesian Optimisation with Gaussian Process Prior Variational Autoencoders
Ramchandran, S., Haussmann, M. & Lähdesmäki, H., 2025, 13th International Conference on Learning Representations, ICLR 2025. Curran Associates Inc., p. 77982-78008 27 p.
Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

Open Access
File
8 Downloads (Pure)
Incorporating hierarchical information into multiple instance learning for patient phenotype prediction with single-cell RNA-sequencing data
Do, C. & Lähdesmäki, H., 1 Jul 2025, In: Bioinformatics. 41, Supplement 1, p. i96-i104
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
File
16 Downloads (Pure)
Latent mixed-effect models for high-dimensional longitudinal data
Ong, P., Haußmann, M., Lönnroth, O. & Lähdesmäki, H., 24 May 2025, In: Transactions on Machine Learning Research. 2025, May, 30 p.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
File
34 Downloads (Pure)

2 Active
11 Finished

AI assisted Health Lähdesmäki: Trustworthy AI-assisted phenotyping, prediction and treatment design using large-scale health data
Lähdesmäki, H. (Principal investigator), Ong, P. (Project Member), Balik, M. (Project Member), Latukka, J. (Project Member), Ögretir, M. (Project Member) & Dumitrescu, A. (Project Member)
01/01/2024 → 31/12/2026
Project: RCF Academy Project targeted call
-: Finnish Center for Artificial Intelligence
Lähdesmäki, H. (Principal investigator)
01/01/2023 → 31/12/2026
Project: Academy of Finland: Other research funding
Heal-Art jatko: Immunoregulation and Therapeutic Precision in Rheumatoid Arthritis
Lähdesmäki, H. (Principal investigator), Osmala, M. (Project Member), Halla-aho, V. (Project Member), Dumitrescu, A. (Project Member), Jokinen, E. (Project Member) & Lankinen, A. (Project Member)
01/01/2021 → 31/12/2022
Project: RCF Academy Project targeted call
-: Bridging the Reality Gap in Autonomous Learning
Lähdesmäki, H. (Principal investigator), Das, A. (Project Member), Solatie, O. (Project Member), Jokinen, E. (Project Member), Korpela, D. (Project Member), Timonen, J. (Project Member), Ögretir, M. (Project Member), Laajala, E. (Project Member) & Iakovlev, V. (Project Member)
01/01/2020 → 31/12/2022
Project: Academy of Finland: Other research funding
FCAI: Finnish Center for Artificial Intelligence (FCAI)
Lähdesmäki, H. (Principal investigator)
01/01/2019 → 31/12/2022
Project: Academy of Finland: Other research funding

Additional file 3 of Probabilistic modeling methods for cell-free DNA methylation based cancer classification
Halla-aho, V. (Creator) & Lähdesmäki, H. (Creator), figshare, 5 Apr 2022
DOI: 10.6084/m9.figshare.19518513, https://springernature.figshare.com/articles/dataset/Additional_file_3_of_Probabilistic_modeling_methods_for_cell-free_DNA_methylation_based_cancer_classification/19518513
Dataset
Additional file 2 of Probabilistic modeling methods for cell-free DNA methylation based cancer classification
Halla-aho, V. (Creator) & Lähdesmäki, H. (Creator), figshare, 5 Apr 2022
DOI: 10.6084/m9.figshare.19518510, https://springernature.figshare.com/articles/dataset/Additional_file_2_of_Probabilistic_modeling_methods_for_cell-free_DNA_methylation_based_cancer_classification/19518510
Dataset
A probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways
Äijö, T. (Creator), Huang, Y.-H. (Contributor), Mannerström, H. (Creator), Chavez, L. (Contributor), Tsagaratou, A. (Contributor), Rao, A. (Contributor) & Lähdesmäki, H. (Creator), figshare, 1 Jan 2016
DOI: 10.6084/m9.figshare.c.3604346.v1, https://figshare.com/collections/A_probabilistic_generative_model_for_quantification_of_DNA_modifications_enables_analysis_of_demethylation_pathways/3604346/1
Dataset
Analyzing Th17 cell differentiation dynamics using a novel integrative modeling framework for time-course RNA sequencing data
Intosalmi, J. (Contributor), Ahlfors, H. (Contributor), Rautio, S. (Contributor), Mannerström, H. (Creator), Chen, Z. (Contributor), Lahesmaa, R. (Contributor), Stockinger, B. (Contributor) & Lähdesmäki, H. (Contributor), figshare, 1 Jan 2015
DOI: 10.6084/m9.figshare.c.3612158.v1, https://figshare.com/collections/Analyzing_Th17_cell_differentiation_dynamics_using_a_novel_integrative_modeling_framework_for_time-course_RNA_sequencing_data/3612158/1
Dataset
LuxHMM: DNA methylation analysis with genome segmentation via hidden Markov model
Malonzo, M. H. (Creator) & Lähdesmäki, H. (Creator), figshare, 13 Apr 2023
DOI: 10.6084/m9.figshare.c.6584741, https://springernature.figshare.com/collections/LuxHMM_DNA_methylation_analysis_with_genome_segmentation_via_hidden_Markov_model/6584741
Dataset

Elias Tillandz prize 2012 for article
Lähdesmäki, H. (Recipient), 2012
Prize: Award or honor granted for a specific work
Elias Tillandz prize 2013 for article
Lähdesmäki, H. (Recipient), 2013
Prize: Award or honor granted for a specific work
IARIA Best Paper Award for our paper
Lähdesmäki, H. (Recipient), 2008
Prize: Award or honor granted for a specific work
Tampere Science Foundation award for the best doctoral thesis
Lähdesmäki, H. (Recipient), 2005
Prize: Award or honor granted for a specific work
The first position in the 5th Dialogue for Reverse Engineering Assessments and Methods (DREAM)
Lähdesmäki, H. (Recipient), 16 Nov 2010
Prize: Award or honor granted for a specific work

4 Membership of an organizing committee or other positions of trust of a conference or a seminar
4 Visiting an external academic institution
2 Statement of assessment of docentship
2 Position of trust in an academic community
More

Faster Bayesian inference in Joint Species Distribution Models
Tikhonov, G. (Speaker), Vanhatalo, J. (Contributor), Ovaskainen, O. (Contributor) & Lähdesmäki, H. (Contributor)
22 Jun 2020 → 26 Jun 2020
Activity: Talk or presentation types › Conference presentation
Foreign Organisation
Lähdesmäki, H. (Visiting researcher)
30 Mar 2016 → 3 Apr 2016
Activity: Visiting an external institution types › Visiting an external academic institution
Foreign Organisation
Lähdesmäki, H. (Visiting researcher)
18 May 2016
Activity: Visiting an external institution types › Visiting an external academic institution
School of Science (Organisational unit)
Lähdesmäki, H. (Member)
Mar 2016 → Jan 2017
Activity: Memberships (typically long-term positions of trust) › Position of trust in an academic community
Foreign Organisation
Lähdesmäki, H. (Visiting researcher)
17 May 2016
Activity: Visiting an external institution types › Visiting an external academic institution

Research Findings from Aalto University Update Understanding of Machine Learning (EPIC-TRACE: predicting TCR binding to unseen epitopes using attention and contextualized embeddings)
Lähdesmäki, H.
27/12/2023
1 item of Media coverage
Press/Media: Media appearance
University of Turku and Abo Akademi University Researchers Target Type 1 Diabetes (Serum APOC1 levels are decreased in young autoantibody positive children who rapidly progress to type 1 diabetes)
Lähdesmäki, H.
10/10/2023
1 item of Media coverage
Press/Media: Media appearance
Research Data from University of Turku and Abo Akademi University Update Understanding of Data Analytics (Permutation-based significance analysis reduces the type 1 error rate in bisulphite sequencing data analysis of human umbilical cord blood ...)
Lähdesmäki, H.
05/10/2023
1 item of Media coverage
Press/Media: Media appearance
Aalto University: Scientists Unravel The Effects Of New Medication For Advanced Melanoma With The Help Of AI
Lähdesmäki, H.
03/03/2023
1 item of Media coverage
Press/Media: Media appearance
Scientists unravel the effects of new medication for advanced melanoma with the help of AI
Lähdesmäki, H.
02/03/2023
2 items of Media coverage
Press/Media: Media appearance

Harri Lähdesmäki

Personal profile

Artistic and research interests

Expertise related to UN Sustainable Development Goals

Keywords

Fingerprint

Collaborations and top research areas from the last five years

Dive into details

Bayesian Basis Function Approximation for Scalable Gaussian Process Priors in Deep Generative Models

E(3)-equivariant models cannot learn chirality: Field-based molecular generation

High-Dimensional Bayesian Optimisation with Gaussian Process Prior Variational Autoencoders

Incorporating hierarchical information into multiple instance learning for patient phenotype prediction with single-cell RNA-sequencing data

Latent mixed-effect models for high-dimensional longitudinal data

AI assisted Health Lähdesmäki: Trustworthy AI-assisted phenotyping, prediction and treatment design using large-scale health data

-: Finnish Center for Artificial Intelligence

Heal-Art jatko: Immunoregulation and Therapeutic Precision in Rheumatoid Arthritis

-: Bridging the Reality Gap in Autonomous Learning

FCAI: Finnish Center for Artificial Intelligence (FCAI)

Additional file 3 of Probabilistic modeling methods for cell-free DNA methylation based cancer classification

Additional file 2 of Probabilistic modeling methods for cell-free DNA methylation based cancer classification

A probabilistic generative model for quantification of DNA modifications enables analysis of demethylation pathways

Analyzing Th17 cell differentiation dynamics using a novel integrative modeling framework for time-course RNA sequencing data

LuxHMM: DNA methylation analysis with genome segmentation via hidden Markov model

Elias Tillandz prize 2012 for article

Elias Tillandz prize 2013 for article

IARIA Best Paper Award for our paper

Tampere Science Foundation award for the best doctoral thesis

The first position in the 5th Dialogue for Reverse Engineering Assessments and Methods (DREAM)

Faster Bayesian inference in Joint Species Distribution Models

Foreign Organisation

Foreign Organisation

School of Science (Organisational unit)

Foreign Organisation

Research Findings from Aalto University Update Understanding of Machine Learning (EPIC-TRACE: predicting TCR binding to unseen epitopes using attention and contextualized embeddings)

University of Turku and Abo Akademi University Researchers Target Type 1 Diabetes (Serum APOC1 levels are decreased in young autoantibody positive children who rapidly progress to type 1 diabetes)

Research Data from University of Turku and Abo Akademi University Update Understanding of Data Analytics (Permutation-based significance analysis reduces the type 1 error rate in bisulphite sequencing data analysis of human umbilical cord blood ...)

Aalto University: Scientists Unravel The Effects Of New Medication For Advanced Melanoma With The Help Of AI

Scientists unravel the effects of new medication for advanced melanoma with the help of AI

Harri Lähdesmäki

Personal profile

Artistic and research interests

Expertise related to UN Sustainable Development Goals

Keywords

Fingerprint

Collaborations and top research areas from the last five years

Research output

Projects

Datasets

Prizes

Activities

Press/Media